一种基于DCT与PCA的奇异值滤波的CT图像噪声抑制算法

A Novel Denoising Approach to SVD Filtering Based on DCT and PCA in CT Image

医学CT图像成像过程中,由于成像机制的影响,不可避免的引入噪声。图像中的噪声会降低图像质量,影响临床诊断。本文提出了一种提高CT图像奇异值分解(SVD)滤波性能的新方法。基于SVD滤波可以有效地分析水平(垂直)方向的图像特性。根据CT图像特征,利用离散余弦变换(DCT)提取图像感兴趣区域,屏蔽不感兴趣区域从而实现图像的结构特征提取,再对DCT变换图像SVD,构造加权函数,自适应地加权重构图像。将本文算法应用于CT图像去噪,实验结果表明,该方法可以有效地提高SVD滤波的性能。

Because of various effects of the imaging mechanism, noises are inevitably introduced in medical CT ima- ging process. Noises in the images will greatly degrade the quality of images and bring difficulties to clinical diagno- sis. This paper presents a new method to improve singular value decomposition （SVD） filtering performance in CT image. Filter based on SVD can effectively analyze characteristics of the image in horizontal （and/or vertical） direc- tions. According to the features of CT image, we can make use of discrete cosine transform （DCT） to extract the re- gion of interest and to shield uninterested region so as to realize the extraction of structure characteristics of the im- age. Then we transformed SVD to the image after DCT, constructing weighting function for image reconstruction a- daptively weighted. The algorithm for the novel denoising approach in this paper was applied in CT image denoising, and the experimental results showed that the new method could effectively improve the performance of SVD filtering.